THE PERFORMANCE OF FUZZY (X)over-bar - R CONTROL CHART FOR MONITORING PROCESS MEAN AND VARIABILITY

The traditional (X) over bar - R control chart and fuzzy (X) over bar - R control chart are used to monitor the process mean and variability. The fuzzy (X) over bar - R control chart was developed by using fuzzy rules for precision manufacturing. The objective of this research is to compare the efficiency of traditional (X) over bar - R and fuzzy (X) over bar - R control charts between traditional method and fuzzy method based on normal distribution. The fuzzy data based on normal distribution with mean (mu) = 10 and variance (sigma(2)) = 1, and the sample size (n) of 5, 10 and 15. The criteria to evaluate the performance of control chart is the average run length for out-of-control process (ARL(1)). The better performance of process is considered with the minimum results of ARL(1). The average run length values are obtained from Monte Carlo simulation technique, repeated 5000 times for each case. The results show that fuzzy (X) over bar - R control chart is more effective than traditional (X) over bar - R control chart for all magnitude of mean shifts.